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LinkedIn is seeking a Principal Staff Software Engineer for Compute Infrastructure in Mountain View, CA. The role focuses on re-architecting the compute stack and scaling workloads in a hybrid work environment.
You will design, build, and operate high-performance scheduling and deployment systems, including large Kubernetes clusters, while coordinating with senior engineering leaders to align infrastructure direction.
LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.
Join us to transform the way the world works.
This role will be based in Mountain View, CA
At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team.
As a Principal Staff Software Engineer of the Compute Infrastructure team at LinkedIn, you will play a crucial role in our ongoing efforts to re-architect our compute infrastructure stack. This is a high-profile, high-impact project that touches every aspect of our engineering organization. We are looking for professionals who have a proven track record of designing large-scale compute infrastructure and driving consensus.
In this role, you will design and implement solutions that enable LinkedIn to scale its compute infrastructure to meet the demands of a rapidly growing user base. This will involve working closely with a team of engineers to develop and operate solutions that are robust, scalable, and efficient. You will also need to work collaboratively with cross-functional teams and be comfortable operating in a fast-paced, dynamic environment.
Responsibilities:
Define the multi-year technical vision for LinkedIn's compute platform, translating company-level priorities into an infrastructure architecture and roadmap.
You will build and operate world class high performance scheduling/deployment solutions including some of the world's largest Kubernetes clusters to place stateless/stateful services, ML workloads and short running jobs efficiently.
You will build and operate a platform that allocates hardware resources with necessary physical/logical distribution for fault tolerance and easy maintenance.
Build alignment across the engineering organization on infrastructure direction, partnering with distinguished engineers, fellows, and senior leadership
Elevate engineering quality org-wide by coaching senior engineers, setting technical standards, and shaping how infrastructure decisions are made at LinkedIn
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $231,000 to $378,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.
The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
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